diff options
Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp')
| -rw-r--r-- | src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp | 22 |
1 files changed, 11 insertions, 11 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp index 69a04df769..6fcb4d0c8b 100644 --- a/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/Conv2dTestImpl.cpp @@ -1,5 +1,5 @@ // -// Copyright © 2017,2022 Arm Ltd and Contributors. All rights reserved. +// Copyright © 2017, 2022, 2024 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // @@ -162,9 +162,9 @@ template<typename T, typename B> void ApplyBias(std::vector<T>& v, float vScale, int32_t vOffset, const std::vector<B>& bias, float bScale, int32_t bOffset, uint32_t w, uint32_t h) { - ARMNN_ASSERT_MSG((armnn::IsQuantizedType<T>() && vScale != 0.0f) || (!armnn::IsQuantizedType<T>()), + CHECK_MESSAGE(((armnn::IsQuantizedType<T>() && vScale != 0.0f) || (!armnn::IsQuantizedType<T>())), "Invalid type and parameter combination."); - ARMNN_ASSERT_MSG((armnn::IsQuantizedType<B>() && bScale != 0.0f) || (!armnn::IsQuantizedType<B>()), + CHECK_MESSAGE(((armnn::IsQuantizedType<B>() && bScale != 0.0f) || (!armnn::IsQuantizedType<B>())), "Invalid type and parameter combination."); // Note we need to dequantize and re-quantize the image value and the bias. @@ -176,7 +176,7 @@ void ApplyBias(std::vector<T>& v, float vScale, int32_t vOffset, for (uint32_t x = 0; x < w; ++x) { uint32_t offset = (i * h + y) * w + x; - ARMNN_ASSERT(offset < v.size()); + CHECK(offset < v.size()); T& outRef = v[offset]; float dOutput = SelectiveDequantize(outRef, vScale, vOffset); outRef = SelectiveQuantize<T>(dOutput + dBias, vScale, vOffset); @@ -233,11 +233,11 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl( bool biasEnabled = bias.size() > 0; // This function currently assumes 1 batch of input/output (and duplicates this into 2 batches). - ARMNN_ASSERT(inputNum == 1); - ARMNN_ASSERT(outputNum == 1); + CHECK(inputNum == 1); + CHECK(outputNum == 1); // If a bias is used, its size must equal the number of output channels. - ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); + CHECK((!biasEnabled || (bias.size() == outputChannels))); // Note these tensors will use two (identical) batches. armnn::TensorInfo inputTensorInfo = @@ -1719,7 +1719,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl( // If a bias is used, its size must equal the number of output channels. bool biasEnabled = bias.size() > 0; - ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); + CHECK((!biasEnabled || (bias.size() == outputChannels))); // Creates the tensors. armnn::TensorInfo inputTensorInfo = @@ -2277,11 +2277,11 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl( bool biasEnabled = bias.size() > 0; // This function currently assumes 1 batch of input/output (and duplicates this into 2 batches). - ARMNN_ASSERT(inputNum == 1); - ARMNN_ASSERT(outputNum == 1); + CHECK(inputNum == 1); + CHECK(outputNum == 1); // If a bias is used, its size must equal the number of output channels. - ARMNN_ASSERT(!biasEnabled || bias.size() == outputChannels); + CHECK((!biasEnabled || (bias.size() == outputChannels))); // Note these tensors will use two (identical) batches. |